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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/19631?offset=650</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30973/abacas</guid>
	<pubDate>Thu, 16 Feb 2017 12:15:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30973/abacas</link>
	<title><![CDATA[ABACAS]]></title>
	<description><![CDATA[<p><span>ABACAS is intended to rapidly contiguate (align, order, orientate) , visualize and design primers to close gaps on shotgun assembled contigs based on a reference sequence. It uses MUMmer to find alignment positions and identify syntenies of assembly contigs against the reference. The output is then processed to generate a pseudomolecule taking overlaping contigs and gaps in to account. MUMmer's alignment generating programs, Nucmer and Promer are used followed by the 'delta-filter' utility function. Users could also run tblastx on contigs that are not used to generate the pseudomolecule.&nbsp;</span></p><p>Address of the bookmark: <a href="http://abacas.sourceforge.net/Manual.html#9._Colour_code" rel="nofollow">http://abacas.sourceforge.net/Manual.html#9._Colour_code</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4098/bioinformatics-algorithm-demonstrations-and-tutorials</guid>
	<pubDate>Thu, 29 Aug 2013 09:23:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4098/bioinformatics-algorithm-demonstrations-and-tutorials</link>
	<title><![CDATA[Bioinformatics Algorithm Demonstrations and Tutorials]]></title>
	<description><![CDATA[<p>Abstract</p>
<p>This project presents demonstrations of selected computer science algorithms important in&nbsp;bioinformatics, implemented in the spreadsheet program Microsoft Excel. Spreadsheets provide an&nbsp;interesting platform for demonstration of algorithms, since various steps of the calculations can be&nbsp;exposed in a manner that is easily comprehensible to users with little programming experience. The&nbsp;algorithms demonstrated include two approaches to approximate string matching (dynamic programming&nbsp;and Shift-AND numeric approximate matching), Hierarchical Clustering (used in phylogenetic studies&nbsp;and microarray analysis of gene expression), a Naive Bayes Classifier for simulated microarray gene&nbsp;expression data, and a simple Neural Network. These demonstrations are designed to serve as&nbsp;instructional aids in bioinformatics courses.</p>
<p>Tutorial @&nbsp;http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsInExcel.zip</p>
<p>One of the best resource for online bioinformatics learning is https://stepic.org/Bioinformatics-Algorithms-2 Enjoy the online learning.</p>
<p>Reference :&nbsp;cybertory</p>
<blockquote>
<p><span>" Please add your favourite bioinformatics algorithms and tutorial links below in the comment section, for the benefit of bioinformatics and computational biology community ".&nbsp;</span></p>
</blockquote><p>Address of the bookmark: <a href="http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsExcelDoc.pdf" rel="nofollow">http://www.cybertory.org/downloads/bae/BioinformaticsAlgorithmsExcelDoc.pdf</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31343/metabat-an-efficient-tool-for-accurately-reconstructing-single-genomes-from-complex-microbial-communities</guid>
	<pubDate>Mon, 06 Mar 2017 03:44:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31343/metabat-an-efficient-tool-for-accurately-reconstructing-single-genomes-from-complex-microbial-communities</link>
	<title><![CDATA[MetaBAT:  An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities]]></title>
	<description><![CDATA[<p>MetaBAT, An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities</p>
<p>Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. Tested on both synthetic and real metagenome datasets, MetaBAT outperforms alternative methods in both accuracy and computational efficiency. Applying MetaBAT to an assembly from 1,704 human gut samples formed 1,634 genome bins (&gt;200kb) in 3 hours, where 621 genome bins are &gt;50% complete with &lt;5% contamination from other species. Further analysis shows that the quality of these genome bins approaches manually curated genomes.</p><p>Address of the bookmark: <a href="https://bitbucket.org/berkeleylab/metabat" rel="nofollow">https://bitbucket.org/berkeleylab/metabat</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</guid>
	<pubDate>Tue, 07 Mar 2017 08:35:12 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31371/phenogram</link>
	<title><![CDATA[PhenoGram]]></title>
	<description><![CDATA[<p><span>With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail.</span></p><p>Address of the bookmark: <a href="http://ritchielab.psu.edu/software/phenogram-downloads" rel="nofollow">http://ritchielab.psu.edu/software/phenogram-downloads</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month</guid>
	<pubDate>Sun, 26 Jul 2015 01:57:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/23498/algorithms-for-dna-sequencing-course-offered-each-month</link>
	<title><![CDATA[Algorithms for DNA Sequencing (course offered each month)]]></title>
	<description><![CDATA[<p>"<span>We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets."</span></p>
<p><span>Source :&nbsp;https://www.coursera.org/course/ads1</span></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://www.coursera.org/course/ads1" rel="nofollow">https://www.coursera.org/course/ads1</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44400/pevzner-lab</guid>
  <pubDate>Thu, 02 Nov 2023 05:39:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pevzner Lab !]]></title>
  <description><![CDATA[
<p>The laboratory works on genome sequencing, immunoproteogenomics, antibiotics sequencing, and comparative genomics - computational technologies that enabled new applications and allowed scientists to attack biological problems that remained beyond the reach of previous techniques.</p>

<p>https://bioalgorithms.ucsd.edu/research4.html</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</guid>
	<pubDate>Wed, 19 Apr 2017 10:09:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32190/dbg2olcefficient-assembly-of-large-genomes-using-long-erroneous-reads-of-the-third-generation-sequencing-technologies</link>
	<title><![CDATA[DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies]]></title>
	<description><![CDATA[<p>DBG2OLC:Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies</p>
<p>Our work is published in Scientific Reports:</p>
<p>Ye, C. et al. DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies. Sci. Rep. 6, 31900; doi: 10.1038/srep31900 (2016).</p>
<p><a href="http://www.nature.com/articles/srep31900">http://www.nature.com/articles/srep31900</a></p>
<p>The manual can be downloaded from:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx">https://github.com/yechengxi/DBG2OLC/raw/master/Manual.docx</a></p>
<p>To use precompiled versions,please go to:</p>
<p><a href="https://github.com/yechengxi/DBG2OLC/tree/master/compiled">https://github.com/yechengxi/DBG2OLC/tree/master/compiled</a></p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://github.com/yechengxi/DBG2OLC" rel="nofollow">https://github.com/yechengxi/DBG2OLC</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</guid>
	<pubDate>Tue, 16 May 2017 08:56:03 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32730/ncbi-prokaryotic-genome-annotation-pipeline</link>
	<title><![CDATA[NCBI Prokaryotic Genome Annotation Pipeline]]></title>
	<description><![CDATA[<p>NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).</p>
<p>Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.</p>
<p>NCBI has developed an automatic prokaryotic genome annotation pipeline that combines&nbsp;<em>ab initio</em>&nbsp;gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP;&nbsp;<a href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=pubmed&amp;dopt=Abstract&amp;list_uids=18416670">see Pubmed Article</a>) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of&nbsp;the pipeline in&nbsp;<a href="https://www.ncbi.nlm.nih.gov/books/NBK174280/">NCBI Handbook chapter</a>. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.</p>
<p>https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/genome/annotation_prok/" rel="nofollow">https://www.ncbi.nlm.nih.gov/genome/annotation_prok/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/2042/ngs-course-medical-genomics-scheduled-for-17-20-september-2013-in-uz-leuven-belgium</guid>
	<pubDate>Mon, 12 Aug 2013 12:08:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/2042/ngs-course-medical-genomics-scheduled-for-17-20-september-2013-in-uz-leuven-belgium</link>
	<title><![CDATA[NGS course Medical Genomics, scheduled for 17-20 September 2013 in UZ Leuven (Belgium).]]></title>
	<description><![CDATA[<p>This course is open to all students and postdocs and registration for all academic participants is free of charge. To help us in organizing the course, please register online via http://gc.uzleuven.be where the preliminary program is also available.</p><p>This course is organized with support from the IAP &ldquo;Belgian Medical Genomics Initiative&rdquo;, SymBioSys and the Genomics Core.</p><p>For inquiries, please email Ms Narcisse Opdekamp ( narcisse.opdekamp@uzleuven.be ).</p><p>More at &gt;&gt;&nbsp;<a href="http://gc.uzleuven.be/">http://gc.uzleuven.be/</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</guid>
	<pubDate>Fri, 09 Aug 2013 13:26:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/1515/list-of-pharmacogenomics-companies-in-india</link>
	<title><![CDATA[List of pharmacogenomics companies in India]]></title>
	<description><![CDATA[<p>pharmacogenomics companies in India are making their good impacts. Here is the list of few pharmacogenomics companies. Please add more if not mentioned here.</p><p>Genomics in India <br /><a href="http://www.ganitlabs.in/">www.ganitlabs.in</a> <br /><a href="http://www.sandor.co.in/">www.sandor.co.in</a> <br /><a href="http://www.igib.res.in/">www.igib.res.in</a> <br /><a href="http://www.genotypic.co.in/">www.genotypic.co.in</a> <br /><a href="http://www.ocimumbio.com/">www.ocimumbio.com</a> <br /><a href="http://www.abcgenomics.com/">www.abcgenomics.com</a> <br /><a href="http://www.xcelrisgenomics.com/">www.xcelrisgenomics.com</a> <br /><a href="http://www.ayugen.com/">www.ayugen.com</a> <br /><a href="http://www.geneombiotech.com/">www.geneombiotech.com</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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